Authors: Isabella C. Richmond1*, Kayleigh Hutt-Taylor1,2, Lauren Bianco1, Antonia Vieira Zanella3, François Bérubé4, Paola Faddoul4, Kelly Vu4, Étienne Perreault-Mandeville5, Patrick Boivin6, Danielle Dagenais6, Nathalie Boucher5, Thi Thanh Hiên Pham4, Carly D. Ziter1
1 Department of Biology, Concordia University, Montreal Canada, H4B 1R6
2 Tree Canada
3 Department of Geography, Federal University of Paraná, Paraná Brazil,
4 Département d’études urbaines et touristiques, Université du Québec à Montréal, Montreal Canada,
5 Organisme Respire
6 École d’urbanisme et d’architecture de paysage, Université de Montréal, Montreal Canada
* isabella.richmond@mail.concordia.ca
Prior predictive checks are used to ensure that the values selected for priors for our models allow a biologically reasonable range of values. For numeric predictor variables, we simulate predictive draws for prior only models and visualize the slope/intercept of the values. We then do a “posterior predictive check” but with the prior only model, to see if the data is captured in the priors. Note that all data is scaled and centered in these data.
For Trois-Rivieres, there is only a categorical predictor variable. Therefore, only the posterior predictive check is presented.